Want to fool a computer vision system? Just tweak some colors

Research into machine learning and the interesting AI models created as a consequence are popular topics these days. But there’s a sort of shadow world of scientists working to undermine these systems — not to show they’re worthless but to shore up their weaknesses. A new paper demonstrates this by showing how vulnerable image recognition models are to the simplest color manipulations of the pictures they’re meant to identify.

It’s not some deep indictment of computer vision — techniques to “beat” image recognition systems might just as easily be characterized as situations in which they perform particularly poorly. Sometimes this is something surprisingly simple: rotating an image, for example, or adding a crazy sticker. Unless a system has been trained…

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